不同树种组的热带森林植被生物量与遥感地学数据之间的相关性分析

以我国云南省西双版纳的热带森林为例,分别对栎类林、其它阔叶林、其它硬阔叶林的生物量与其对应的Landsat TM数据及其派生数据、气象数据和地形数据进行了相关性分析。首先,利用森林资源连续清查的林业固定样地数据,通过各树种组的各器官生物量估算模型计算出各样地的森林植被的生物量。然后,根据样地的坐标来建立样地GIS数据库。其次,将同期的遥感影像、气象数据和地形数据与GIS数据进行配准,并从遥感影像中产生出一系列的派生数据。最后,在此基础上,分别对栎类林、其它阔叶林、其它硬阔叶林的样地生物量与其遥感数据和派生数据、气象数据和地形数据进行相关性分析。研究表明,栎类林的生物量与TM1、TM2、TM3、TM4、TM5、TM7、缨帽变换的亮度、绿度、湿度、VI3、DVI、PC1和PVI在0.05的水平上显著,而与其它因子在这个水平上相关都不够显著。其它阔叶林的生物量与降雨量在0.05的水平上显著,而与其它因子在这个水平上相关都不够显著。其它硬阔叶林的生物量与降雨量在0.05的水平上显著,而与其它因子在这个水平上,其相关都不够显著。

The Correlation Analysis of the Landsat TM Data,Its DerivedData,Meteorological Data and Topographic Data with theBiomass of the Tropical Forest Vegetation ofDifferent Forest

correlation analysis of the Landsat TM data, its derived data, meteorological data andtopographic data with the biomass of the tropical forest vegetation for the lithocarpus forest, the otherbroad leaf forest and the hard broad-leaf forest is explored here in Xishuangbanna, Yunnan province, P.R.of China. It includes four steps. Firstly, the biomass for each forest sample is calculated by using thefield inventory data of each sample. Secondly, GIS Database is established according the coordinate of eachforest sample. Secondly, Remote sensing image and its derived data, meteorological data, topographicaldata and the biomass of each sample are referenced to the same projection and coordination. Finally, thecorrelation between the Landsat TM and its derived data, meteorological data, topographical data and thebiomass is analyzed respectively for the lithocarpus forest, the other broad leaf forest and the hard broad-leaf forest. It is shown as follows: (1) The correlations of the biomass of lithocarpus forest and LandsatTM1,TM2,TM2,TM4,TM5,TM7,Bright,Green,Wet,VI3,DVI,PC1 and PVI are obvious at 0.05 level.(2) The correlation between the biomass of the other broad leaf forest and average rainfall per year isobvious at level 0.05. (3)The correlation of the biomass of the hard broad-leaf forest and average rainfallper year is obvious at level 0.05.Key words: